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index.html
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<!doctype html>
<html>
<head>
<meta charset='UTF-8'><meta name='viewport' content='width=device-width initial-scale=1'>
<title>神经网络与深度学习</title><link href='https://fonts.loli.net/css?family=Open+Sans:400italic,700italic,700,400&subset=latin,latin-ext' rel='stylesheet' type='text/css' /><style type='text/css'>html {overflow-x: initial !important;}:root { --bg-color:#ffffff; --text-color:#333333; --select-text-bg-color:#B5D6FC; --select-text-font-color:auto; --monospace:"Lucida Console",Consolas,"Courier",monospace; }
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<div id='write' class = 'is-node'><h1><a name="神经网络与深度学习" class="md-header-anchor"></a><span>神经网络与深度学习</span></h1><p><span>作者：</span><a href='https://xpqiu.github.io/'><span>邱锡鹏</span></a><span> 微博：</span><a href='http://weibo.com/xpqiu'><span>@邱锡鹏</span></a></p><h2><a name="关于本书" class="md-header-anchor"></a><span>关于本书</span></h2><p><span>近年来，以机器学习、知识图谱为代表的人工智能技术逐渐变得普及。从车牌识别、人脸识别、语音识别、智能问答、推荐系统到自动驾驶，人们在日常生活中都可能有意无意地使用到了人工智能技术。这些技术的背后都离不开人工智能领域研究者们的长期努力。特别是最近这几年，得益于数据的增多、计算能力的增强、学习算法的成熟以及应用场景的丰富，越来越多的人开始关注这一个“崭新”的研究领域：</span><em><span>深度学习</span></em><span>。深度学习以神经网络为主要模型，一开始用来解决机器学习中的表示学习问题。但是由于其强大的能力，深度学习越来越多地用来解决一些通用人工智能问题，比如推理、决策等。目前，深度学习技术在学术界和工业界取得了广泛的成功，受到高度重视，并掀起新一轮的人工智能热潮。</span></p><p><span>本课程主要介绍神经网络与深度学习中的基础知识、主要模型（前馈网络、卷积网络、循环网络等）以及在计算机视觉、自然语言处理等领域的应用。</span></p><p><span>要获取更新提醒，请关注</span><a href='https://github.com/nndl/nndl.github.io' target='_blank' class='url'>https://github.com/nndl/nndl.github.io</a></p><p><span>课程练习，见</span><a href='https://github.com/nndl/exercise' target='_blank' class='url'>https://github.com/nndl/exercise</a></p><p><span>豆瓣评分：</span><a href='https://book.douban.com/subject/33409947/' target='_blank' class='url'>https://book.douban.com/subject/33409947/</a></p><h2><a name="概要" class="md-header-anchor"></a><span>概要</span></h2><p><strong><span>全书内容</span></strong><span> </span><a href='nndl-book.pdf'><span>pdf</span></a><span> (updated 2020-02-11) （推荐用iPad阅读）</span></p><p><span>更新说明：</span><a href='https://github.com/nndl/nndl.github.io' target='_blank' class='url'>https://github.com/nndl/nndl.github.io</a></p><p><span>《神经网络与深度学习》3小时课程概要 </span><a href='./ppt/神经网络与深度学习-3小时.pptx'><span>ppt</span></a><span>(72M) </span><a href='./ppt/神经网络与深度学习-3小时.pdf'><span>pdf</span></a><span> (12M) </span></p><h3><a name="章节内容" class="md-header-anchor"></a><span>章节内容</span></h3><ol start='' ><li><span>绪论[</span><a href='./ppt/chap-绪论.pptx'><span>ppt</span></a><span>] </span></li><li><span>机器学习概述 [</span><a href='./ppt/chap-机器学习概述.pptx'><span>ppt</span></a><span>] </span></li><li><span>线性模型 [</span><a href='./ppt/chap-线性模型.pptx'><span>ppt</span></a><span>] </span></li><li><span>前馈神经网络 [</span><a href='./ppt/chap-前馈神经网络.pptx'><span>ppt</span></a><span>] </span></li><li><span>卷积神经网络 [</span><a href='./ppt/chap-卷积神经网络.pptx'><span>ppt</span></a><span>] </span></li><li><span>循环神经网络 [</span><a href='./ppt/chap-循环神经网络.pptx'><span>ppt</span></a><span>] </span></li><li><span>网络优化与正则化 [</span><a href='./ppt/chap-网络优化与正则化.pptx'><span>ppt</span></a><span>] </span></li><li><span>注意力机制与外部记忆 [</span><a href='./ppt/chap-注意力机制与外部记忆.pptx'><span>ppt</span></a><span>] </span></li><li><span>无监督学习 [</span><a href='./ppt/chap-无监督学习.pptx'><span>ppt</span></a><span>] </span></li><li><span>模型独立的学习方式 [</span><a href='./ppt/chap-模型独立的学习方式.pptx'><span>ppt</span></a><span>] </span></li><li><span>概率图模型 [</span><a href='./ppt/chap-概率图模型.pptx'><span>ppt</span></a><span>] </span></li><li><span>深度信念网络 [</span><a href='./ppt/chap-深度信念网络.pptx'><span>ppt</span></a><span>] </span></li><li><span>深度生成模型[</span><a href='./ppt/chap-深度生成模型.pptx'><span>ppt</span></a><span>] </span></li><li><span>深度强化学习 [</span><a href='./ppt/chap-深度强化学习.pptx'><span>ppt</span></a><span>] </span></li><li><span>序列生成模型 [</span><a href='./ppt/chap-序列生成模型.pptx'><span>ppt</span></a><span>] 一个过时版本：</span><a href='chap-语言模型与词嵌入.pdf'><span>词嵌入与语言模型</span></a></li><li><span>数学基础 </span></li></ol><h2><a name="反馈意见" class="md-header-anchor"></a><span>反馈意见</span></h2><p><span>如果您有任何意见、评论以及建议（先确认最新版本中是否已经修正），请通过GitHub的</span><a href='https://github.com/nndl/nndl.github.io/issues'><span>Issues</span></a><span>页面进行反馈。如果错误比较重要，我会在本书中进行致谢。</span></p><p><span>反馈意见包括但不限于：（因为分开排版关系，页码错误请忽略。）</span></p><ul><li><span>打字错误</span></li><li><span>描述错误: 比如“感知器是非线性分类器”</span></li><li><span>评论</span></li><li><span>建议</span></li></ul><p><span>非常感谢！</span></p><p><span>致谢列表：感谢王利锋、林同茂、张钧瑞、李浩、胡可鑫、韦鹏辉、徐国海、侯宇蓬、任强、王少敬、肖耀、李鹏等同学指出书中的错误。</span></p></div>
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